Individual-focused approaches to the prevention of college student drinking.

Alcohol consumption is prevalent among college students and can become problematic for some. Numerous randomized controlled trials have evaluated the efficacy of individual preventive interventions in reducing alcohol use and alcohol-related problems in college student populations. Consistent with earlier reviews, the balance of the evidence from studies conducted during the past 3 years strongly supports the efficacy of brief motivational interventions combined with personalized feedback interventions (PFIs) and personalized normative feedback (PNF), as well as of stand-alone PFI/PNF interventions. Recent analyses also continue to support the efficacy of alcohol expectancy challenge interventions, although the findings are less consistent. In addition, recent analyses offer mixed support for feedback-based interventions focused solely on blood alcohol concentration and for multicomponent, alcohol education-focused interventions that include elements of PFI/PNF. No evidence of efficacy was found for programs that only included alcohol education.

A s detailed by Johnston and colleagues (2009), the majority of young adults, in particular college stu dents, consume alcohol. Moreover, a substantial proportion of those who consume alcohol misuse it, engag ing in heavy episodic drinking, 1 which directly and indirectly contributes to a host of harmful consequences (O'Malley and Johnston 2002;Perkins 2002). The rates of heavy drinking peak at ages 21 or 22 (Johnston et al. 2009), suggesting that most college students mature out of heavy drinking. Nevertheless, the harm they experience as a result of heavy drinking, such as poor academic and work perfor mance or serious physical injury, may irrevocably alter students' natural developmental trajectories. In an effort to prevent or mitigate such longterm harm, myriad prevention programs have been developed to reduce college student drinking by targeting individual factors associated with alcohol use and misuse, including alcohol expectancies, drinking motives, perceived norms, and natural ambivalence regarding behavior (Baer 2002;Presley et al. 2002). A wealth of research has been devoted to evaluating the efficacy of these preventive interventions. The purpose of this article is to provide a comprehensive summary of the current state of the science with regard to individualfocused preventive interventions whose efficacy in reducing alcohol use and alcoholrelated problems has been evaluated in the college student popula tion using randomized controlled trials. Conclusions from earlier reviews in this area are described briefly, with greater focus given to summarizing evidence accumulated in the past 3 years (2007)(2008)(2009)(2010). Cronce (2002, 2007) conducted qualitative reviews of research published between 1984 and early 2007 that evaluated the efficacy of individual preventive interventions aimed at college students. Both reviews noted a dearth of support for educational or awareness models, including informationbased and valuesclarification approaches, whereas there was evidence of efficacy for skillsbased interventions, including selfmonitoring/ assessment, alcohol expectancy challenge (AEC), and multicomponent skills training. Moreover, both reviews documented strong empirical support for brief motiva tional interventions (BMIs) delivered via mail, online, or in person. As the name implies, inperson BMIs are brief (i.e., typically delivered over one or two sessions) and focus on enhancing motivation and commitment to change problematic behavior. To this end, BMIs often provide personalized feedback regarding the client's drink ing and related consequences, alcohol expectancies, and drinking motives; when delivered alone in the absence of a trained facilitator, this personalized feedback component is referred to as a personalized feedback intervention (PFI). BMIs and PFIs often additionally include general alcohol information (i.e., alcohol education) and alcohol specific coping and harmreduction skills. PFIs typically include personalized normative feedback (PNF), which compares the client's selfreported drinking behavior to the average drinking behavior of a specific reference group (e.g., typical student, typical female). PNF encourages clients to explore and enhance discrepancies between their perception of their own drinking as "typical" and the actual drinking behaviors of their peers-that is, that the JESSICA M. CRONCE, PH.D., is a senior postdoctoral fellow, and MARY E. LARIMER, PH.D., is a professor in the Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, Washington. 1 The National Institute on Alcohol Abuse and Alcoholism (NIAAA) defines binge or heavy episodic drinking as the consumption of an amount of alcohol leading to a blood alcohol concentration (BAC) of 0.08 percent, which, for most adults, would be reached by consuming five drinks for men or four for women over a 2hour period (NIAAA 2004). Wechsler and colleagues (1995) similarly denote a binge episode as consumption of five or more drinks for men and four or more drinks for women but do not stipulate a bounded time frame during which consumption must occur or link the episode to a particular BAC. The latter definition by Wechsler and colleagues (1995) was used most frequently across the studies reviewed here. majority of students drink moderately, often significantly less than the individual receiving the intervention. Like PFIs, PNF can be delivered as a standalone intervention in the absence of inperson contact. Larimer and Cronce (2007) independently detailed empirical evidence sup porting normative reeducation interventions, in particular computeradministered or inperson PNF interventions, that produced reductions in drinking and/or consequences mediated through changes in normative perceptions.

Previous Reviews
Complementing the qualitative reviews by Cronce (2002, 2007), Carey and colleagues (2007) conducted a quantitative review evaluating 62 randomized clinical trials of 98 alcohol interventions for college students published dur ing roughly the same time period (i.e., 1985 to early 2007). This metaanalysis similarly supported the efficacy of individual focused alcohol interventions in reducing the quantity and frequency of alcohol use and alcoholrelated negative conse quences. The investigators further noted that significant intervention effects on indices of alcohol consumption peaked before the 6month followup and that subsequently emerging effects on alcoholrelated negative consequences lasted through longterm followup (ranging from 1 to 3.75 years). Specifically, Carey and colleagues (2007) concluded that individual interventions that used motivational inter viewing techniques, included personalized feedback on alcohol expectancies and drinking motives with normative reeducation components, and included decisional balance exercises demonstrated greater efficacy in reducing alcohol related consequences than did various comparison groups. This combination of intervention components is common to intervention approaches patterned after the Brief Alcohol Screening and Intervention for College Students (BASICS) program (Dimeff et al. 1999).

Review of Recent IndividualFocused Preventive Intervention Studies
In the years since the publication of the reviews by Carey and colleagues (2007) and Cronce (2002, 2007), numerous studies of individualfocused preventive interventions for college student drinking have been published. Of these, 36 studies evaluating 56 unique interventions, met criteria for inclusion in this review (see the tables for details). Studies were identified via a comprehensive search of electronic databases, including PsycINFO and MEDLINE (for a list of search terms used, see Larimer and Cronce 2007), covering the period from late 2007 to early 2010. Additional studies were identified indirectly (e.g., they were referenced in the introduction section of one of the identified studies), and asyetunpublished studies were provided directly by authors. Studies were included if they used a randomized controlled trial approach-that is, if they randomly assigned individual participants (or intact groups) to one of two or more experimental conditions, including at least one active intervention and an ostensibly inert control (e.g., assess ment only) group. Although the number of studies meet ing inclusion criteria suggests that a metaanalysis may be warranted, a qualitative approach was selected for this review to facilitate more rapid communication with key stakeholders concerning the current state of alcohol pre vention. 2 However, intervention effect sizes are reported for relevant outcomes in all studies that included effect size estimates in the original report or provided sufficient postintervention data to calculate betweengroup estimates (see tables). Withingroup effect size estimates also are pro vided for studies wherein significant withinperson reduc tions in alcohol use or consequences were evident.
Many of the studies included in this review evaluate the efficacy of multicomponent BMIs, many of which were adapted from the BASICS program. Most of these BMIs incorporated a PFI with PNF. Some studies evaluated one or more PFI/PNF interventions delivered alone, without the benefit of a trained intervention facilitator. Interventions were delivered via various modalities, including inperson group and individual sessions, mailed printed material, and Webbased content. In addition, some interventions were conducted in special settings (i.e., primary care, in the student's home before entering college) or targeted highrisk student subpopulations (i.e., mandated/ sanctioned students, freshmen, or athletes).

StandAlone PFI/PNF Interventions.
A total of 17 studies evaluated the impact of 14 unique PFIs/PNF and 4 PNF only interventions implemented via written material, mail, computer, Web, or electronic diary on college student drinking (see table 1). Of 14 PFI/PNF interventions eval uated, 6 were associated with reductions in drinking but not drinkingrelated consequences relative to the comparison condition at followup. One PFI/PNF intervention (Doumas and Andersen 2009) was associated with reduced drinking related consequences as well as alcohol use. Four additional PFI/PNF interventions were associated with significant withinperson reductions in alcohol use and/or consequences across assessment periods, but betweengroup differences were not evident. Of four PNFonly interventions evaluated, three resulted in reductions in drinking outcomes at fol lowup. The remaining PNFonly intervention had no effects on these outcomes but was associated with reductions in perceived drinking norms and increased readiness/ preparation for behavior change.
InPerson BMIs. The literature review also identified 17 studies evaluating 20 unique inperson BMIs (individual and group), most of which incorporated PFI and/or PNF (see table 2). Of these interventions, 13 were associated continued on page 218 2 Both metaanalytic (quantitative) and qualitative reviews seek to combine findings from multiple studies addressing a shared research hypothesis (e.g., that a particular type of intervention will reduce alcohol use and/or consequences). In a metaanalysis, findings are combined via a com mon measure of effect size (e.g., Cohen's d), and conclusions are based on a weighted average of all of the effect sizes. By comparison, a qualitative approach is more inductive, and conclusions summarize the balance of the evidence based on an additive evaluation of the separate studies.  White et al. (2007); as such, these interventions are not included in the total count of unique interventions provided in the text. Intervention conditions followed by an " *" indicates the specific intervention was associated with reductions, or exhibited a protective effect against, relevant behavioral outcomes (e.g., quantity or frequency of alcohol consumption; alcoholrelated negative consequences). Effect sizes reported include Cohen's d (Cohen, 1988), which denotes the standardized difference between the mean of the intervention and comparisons groups and eta squared (η2), which denotes the proportion of total variability in the dependent variable attributable to the effect of the independent variable, or partial eta squared (ηp2). According to Cohen's (1988Cohen's ( , 1992 definitions of effect size, small, medium, and large effects for d are considered to be in the 0.20, 0.50, and 0.80 ranges, respectively, and for η2 and ηp2 are 0.01, 0.06, and 0.14, respectively. N/A = effect size estimate not available. women only (1) gram (Alcohol 101 Plus) NOTE: conditions followed by an "*" indicates the specific intervention was associated with reductions, or exhibited a protective effect against, relevant behavioral outcomes (e.g., quantity or frequency of alcohol con sumption; alcoholrelated negative consequences). Mun et al. (2009) andLaBrie et al. (2009) both reported the outcome of subsequent analyses related to the efficacy of interventions originally reported in White et al. (2007) and LaBrie et al. (2008), respectively; as such, these interventions are not included in the total count provided in the text. Effect sizes reported include Cohen's d (Cohen, 1988), which denotes the standardized difference between the mean of the intervention and comparisons groups, Cohen's h (Cohen, 1988), which denotes the difference between two proportions, and eta squared (ηp2), which denotes the proportion of total variability in the dependent variable attributable to the effect of the independent variable, or partial eta squared (ηp2). According to Cohen's (1988Cohen's ( , 1992 definitions of effect size, small, medium, and large effects for d and h are considered to be in the 0.20, 0.50, and 0.80 ranges, respectively, and for η2 and ηp2 are 0.01, 0.06, and 0.14, respectively. N/A = effect size estimate not available.  (1) No group differences on alcohol use or consequences (1,2) NOTE: conditions followed by an "*" indicates the specific intervention was associated with reductions, or exhibited a protective effect against, relevant behavioral outcomes (e.g., quantity or fre quency of alcohol consumption; alcoholrelated negative consequences). Effect sizes reported include Cohen's d (Cohen, 1988), which denotes the standardized difference between the mean of the intervention and comparisons groups, Cohen's h (Cohen 1988), which denotes the difference between two proportions, and eta squared (η2), which denotes the proportion of total variability in the dependent variable attributable to the effect of the independent variable, or partial eta squared (ηp2). According to Cohen's (1988Cohen's ( , 1992 definitions of effect size, small, medium, and large effects for d and h are considered to be in the 0.20, 0.50, and 0.80 ranges, respectively, and for η2 and ηp2 are 0.01, 0.06, and 0.14, respectively. NA = effect size estimate not available. with reductions in drinking, alcoholrelated negative consequences, and/or associated psychopathology, and three interventions exhibited a protective effect against the onset of or increase in alcohol use and/or related consequences. One of these studies (Schaus et al. 2009) demonstrated a sleeper effect of the intervention, with shortterm reductions in drinking and subsequently emerging reductions in con sequences. Also note that another of these studies (Doumas and Hannah 2008) was not specifically aimed at college students but targeted young adults (ages 18 to 24) who were employed; however, 75 percent of the sample con currently was enrolled in school. This study found that BMI combined with PFI was equivalent to PFI alone in reducing drinkingrelated variables. Finally, one of these studies (Hansson et al. 2007) specifically evaluated inter vention gains between the 12month and 24month fol lowup and found an advantage for a BMI combined with coping skills over either component alone. A quantitative comparison of changes from baseline to the 12month followup was not presented. However, figures displaying group means suggest a potential short term effect of the BMIonly condition in reducing estimated blood alcohol concentrations (BACs), which, if counted, would bring the above total support for BMI conditions from 13 to 14.
Other conclusions that can be drawn from the analysis of these studies include the following: • Findings of studies evaluating BMI in specialized settings and highrisk subpopulations suggest that primary care is an effective venue for delivery of this type of intervention (Schaus et al. 2009).
• Group BMI or BMI enhanced with parental coaching is effective in reducing drinking among college freshmen (Turrisi et al. 2009;Wood et al. 2010).
• Studies involving students who had been mandated to participate in the interventions documented benefits of BMIs (Carey et al. 2009;White et al. 2007), in particular for females (Carey et al. 2009) and those who received additional services, including coping skills, problem solving, and stress management training, in the context of a student assistance program (Amaro et al. 2009). Another study (Carey et al. 2010) additionally found greater benefit of BMI participation in reducing alcohol consumption among female mandated students compared with two separate multicomponent educational programs; however, reductions in the BMI were similar to assessment only. Participation in any of the three interventions was associated with short term reductions in alcohol consumption among male mandated students.

Other Preventive Approaches.
Additional studies evaluated other specific alcohol interventions, in most cases comparing these approaches to other active interventions (e.g., BMI or PFI/PNF) (see table 3). Two studies published in the time period evaluated included alcohol expectancy challenge (AEC) protocols, which generally are considered to be more skills based than motivational in nature. LauBarraco and Dunn (2008) evaluated a singlesession, genderspecific in vivo (experiential) AEC. In contrast, Wood and col leagues (2007) assessed a twosession mixedgender in vivo AEC, both alone and in combination with a BMI involving a PFI/PNF component. Both AEC interventions resulted in reductions in alcohol use but not alcohol consequences. Two other studies (Glindemann et al. 2007;Thombs et al. 2007) investigated the efficacy of BAC feedback, another cognitive-behavioral skillsbased approach used to intervene with college students. One of these studies (Glindemann et al. 2007) demonstrated a positive effect of the intervention (i.e., reductions in BACs), whereas the other (Thombs et al. 2007) reported a potential inadvertent opposite (i.e., iatro genic) effect-that is, an increase in BACs. These mixed findings may be related to differences between the two studies in terms of the timing of the feedback (i.e., imme diate versus delayed) and use of incentives to promote lower BACs (i.e., a $100 cash raffle for participants with BACs lower than 0.05 percent in the study by Glindemann and colleagues [2007]).
Four studies evaluated alcohol education either as a standalone intervention (see Thadani et al. 2009) or as a comparison intervention for PFI/PNF interventions with or without BMI. These studies generally found increases in alcohol knowledge among the students receiving the intervention. However, the interventions generated equivocal or negative effects on alcohol use and related consequences because they detected no group differences and/or lacked an assessmentonly control group.
Finally, eight studies tested nine unique multicomponent, educationfocused programs, which included general alcohol information as well as elements typically associated with efficacious BMI and PFI/PNF interventions, such as per sonalized feedback, normative reeducation, challenge of positive drinking expectancies, and tips for harm reduction. Just over onehalf of these programs were associated with reductions in drinking and/or alcohol consequences, whereas the remainder (i.e., Alcohol 101 Plus [Carey et al. 2009]; an inperson, facilitatorled program [Cimini et al. 2009

IndividualFocused Preventive Interventions: Conclusions and Future Research
In summary, studies published between 2007 and early 2010 provide consistent support for the efficacy of brief, personalized, individual motivational feedback (i.e., BMI with PFI/PNF) interventions and standalone PFI/PNF interventions. These studies also provide support for the efficacy of AEC interventions, although less consistent, and offer mixed support for BAC feedback. These conclu sions are in line with previous reviews (Carey et al. 2007;Cronce 2002, 2007). Also consistent with previous reviews, there was an absence of support for programs solely including alcohol education, although multicompo nent alcohol education-focused programs, which combine educational elements with BMI, PFI, and PNF components, had greater, albeit mixed, support.
Although the balance of the evidence supports the efficacy of PFI/PNFonly interventions, additional research on these interventions is necessary to identify the elements and/or modalities that are associated with behavior change and to determine for whom inperson BMI is more (or less) efficacious compared with PFI/PNFonly interventions. The lack of intervention effects in a few of the BMI and PFI/PNF studies may reflect the potential absence (or ineffective delivery) of necessary intervention components or the presence of potential moderators of intervention effects (e.g., mandated student status). Additional research also needs to establish the efficacy of these brief interventions in reducing longterm risk. Thus, it may be necessary to modify and evaluate existing interventions and/or evaluate the effects of supplemental interventions in order to extend their shortterm effects and enhance or prolong their impact on negative drinking consequences. Recent findings (Carey et al. 2007;Schaus et al. 2009) suggesting longer term emergent effects on alcoholrelated consequences, particularly in response to inperson BMIs (Carey et al. 2007), indicate that the addition of longerterm followup assessments will be necessary to achieve this. Finally, addi tional research is needed to evaluate the efficacy of BMIs in combination with other interventions, including inter ventions targeting environmental change, parenting prac tices, or psychiatric comorbidity. Ultimately, multiple intervention strategies may be necessary to produce lasting effects on college student drinking and related harm.
Unfortunately, key stakeholders (e.g., college adminis trators, campus health professionals) face numerous barriers when trying to implement efficacious individualfocused alcohol interventions. For example, with the exception of commercially available programs, such as eChug or AlcoholEdu, the measures and feedback programs used in most intervention protocols are not easily accessible or not immediately useable. For those seeking to implement the BASICS approach (Dimeff et al. 1999), a published manual and measures are available. However, campus personnel may not have adequate resources (e.g., the expertise to train and supervise therapists, access to programs that can generate personalized feedback, or access to campus specific nor mative drinking data) to implement the program with sufficient fidelity.
Many of these barriers can be overcome by pairing health and counseling personnel with faculty in academic depart ments who may have experience with program evaluation and implementation. Word processing and spreadsheet/ database programs generally available to campus personnel can be used to generate basic personalized feedback. Distancelearning methods currently used to disseminate some evidencebased public health interventions (e.g., video or Webbased conferencing of initial training and ongoing clinical supervision) could be adapted to support implementation of BMI protocols. Implementation of routine alcohol screening in campus health centers could be used to gather normative data for use in PFI/PNF and to identify students appropriate for intervention.
Barriers to intervention implementation also necessitate additional research into increasing the reach of evidence based approaches. This includes research related to train ing of providers and assessment of fidelity for inperson interventions, methods to improve impact and portability of Webbased or mailed/written interventions, and research on adaptation of efficacious interventions so they are appropriate for young adults from different cultural backgrounds and in contexts outside the traditional, mainstream college setting. To date, young adults in the workplace, communitycollege settings, tribal colleges and universities, historically Black colleges and universi ties, and other minorityserving institutions have been substantially underrepresented in efficacy trials of BMIs and related interventions. Careful consideration and the development of meaningful community partnerships to support the bidirectional learning necessary to adapt and implement efficacious brief prevention approaches in these settings are needed. ■